Tag Archives: homophily

Social capital is a powerful resource for individuals and communities. For individuals embedded in dense social networks, these networks and the attendant norms of trust and reciprocity strongly shape individuals’ ability to land jobs, earn higher salaries, and be happier and healthier. But, even for those not in the networks, having neighbors who know and trust one another affords benefits in some domains: better performing local government, safer streets, faster economic growth and better performing schools, among other public goods.

For sure social capital can be used toward negative ends: Al Qaeda, the Crips and the Bloods, the Michigan Militia are all examples where group members can accomplish things that they could not accomplish individually (because of group social capital). That said, the literature supports that the vast majority of what social capital is used for is to produce positive ends, not negative ones.

But why? What makes social capital so powerful?

Robert Putnam and I had always focused on information-flows as the key mechanism. So these social networks:

enable individuals to access valuable information: how to get something done, hear of job leads, learn how better to promote one’s health, find out what is happening in a community, etc.; or

help individuals find partners for joint economic transactions (e.g., to know with whom to partner in business, to close a sale to a friend or a friend of a friend, to locate a neighbor with whom one can exchange tools or expertise); or

spread reputations of members (or neighbors or local merchants) which causes all people in these networks to behave in a more trustworthy manner and facilitates altruism. There is always a short-term gain to be had from cheating someone, but if the social networks quickly spread the information that one cannot be trusted, this short-term gain is swamped by the lost future opportunity to do business with others; thus it becomes more rational to be honest and trustworthy in communities (physical or otherwise) with strong social networks. Individuals are also likely to be kinder and more altruistic toward others because they know that “what goes around comes around” in densely inter-connected networks and communities; and

facilitate collective action: it is easier to mobilize others around some shared goal like politics or zoning or improving trash pick-up if others in the community already know and trust you, rather than your having to build those social relationships from scratch.

But Connected (by Nick Christakis and James Fowler) raises a different frame for thinking about this issue: network effects or contagion. Are there properties of the networks themselves that help spread practices, independent of the flow of information? This is difficult to answer fully since much of their evidence comes from the Framingham Heart Study where they know who people’s friends are but not what they are doing with each other or what they are saying to each other.

That said, some of their results can be explained by information flows (e.g., political influence, or getting flu shots), but some seem likely to be working through other channels and not through information-flows (e.g., happiness or loneliness cascades).

In these “network effects” or contagion, Fowler & Christakis typically find that the strongest “network” effects are directly with one’s friends (one degree of separation), but these effects also ripple out two more levels to friends of one’s friends (two degrees) and friends of the friends of one’s friends (three degrees). As one would expect, much like a stone dropped in a pond, the ripples get smaller as one moves out. In fact they refer to the “Three Degrees of Influence” Rule that effects are typically only seen up to three degrees out and not further: in the spread of happiness, political views, weight gain, obesity, and smoking. For example, in happiness, if one is happy, one degree out (controlling for other factors), one’s friends are 15% happier, at 2 degrees of separation they are 10% happier, and they are 6% happier at 3 degrees of separation. For obesity, the average obese American is more likely to have obese friends, one, two and three degrees of separation out, but not further. Quitting smoking has diminishing effects out to three degrees. For political influence, they note a “get-out-the-vote” experiment that shows that knocking on a stranger’s door and urging the resident to support a recycling initiative had a 10% impact on his/her likelihood to vote for the initiative; what was noteworthy to Christakis and Fowler is that the door-knocking made the spouse (who was not at the door) 6% more likely to support the recycling initiative based on communication with his/her spouse. They conjecture that if this 60% social pass-through rate of political appeals (6% for spouse vs. 10% for person answering door) applied to one’s friends and if everyone had 2 friends, then one person urging friends to vote a certain way would have a 10% impact on one’s friends, a 6% impact on one’s friends’ friends (2 degrees) and a 3.6% impact 3 degrees out. Multiplying these political effects all the way through, one vote could create a 30x multiplier. [The example is eye-opening and suggests that voting and political persuasion may be less irrational than thought, but also is based on a huge number of assumptions and assumes no cross-competing messages from friends.]

In an experiment on altrusim (explained in this post) Christakis & Fowler found that $1.00 of altruism, ultimately produced $1.05 of multiplier effect ($.20 one ripple out with 3 others and $.05 of altruism two ripples out with 9 others).

Christakis and Fowler, in their book, talk about contagion effects in voting, suicide, loneliness, depression, happiness, violence, STDs, number of sexual partners, binge drinking, back pain, and getting flu shots, among others. [One summary of many of their findings, which they note, is “You make me sick!”]

1) intrinsic decay: C&F liken this to a game of telephone where as the information gets repeated, the content gets lost, or the passion and knowledge of the initiator gets dissipated.

2) Instability of ties: because of what is known as “triadic closure“, if A is friends with B and B is friends with C, it is likely that A will become friends with C. Because of this, closer-in ties between people have more routes connecting them, and further out ties are more dependent on only one pathway connecting them. For example, assume Abby and Fran were friends 3 degrees removed via Bert and via Charles. If any of these intervening friendships end (say Bert is no longer friends with Charles), Abby loses her tie to Fran. Thus, these outer ties are much less stable and averaged across all the “3 degrees of influence” friendships, many more may have zero effect because the path of influence dies out as friends change.

3) cross-information: as one gets further out away from you, say the friends of the friends of your friends, all of these folks are getting lots of cross-stimuli from lots of other sources (many of which may come from different clusters with different habits or values) and these cross-stimuli start to cancel each other out.

4) evolutionary biology: C&F note that humans evolved in small groups that had a maximum of three degrees of separation so it may be that we became more attuned to being influenced by folks who were in a position to alter our gene pool.

So what are the network influences independent of communication. There seem like 6 possible channels, and often it is hard to separate one from the other, although some may make more sense for the spread of behaviors and others may make more sense for spread of attitudes or emotions:

1) homophily: “Homophily” is the practice of befriending others like you — “birds of a feather flock together.” Being friends with people who are different than you can be stressful. This is why in mates and in friends we are likely to choose others with whom we have a lot in common — think of arguments you’ve had with friends about where to go for dinner or what is right or wrong with the world when those friends have very different tastes or politics. For this reason, one reason for increased clustering over time of obese people or smokers or binge drinkers is that it is stressful to be in groups where one is the minority and either constantly noodging others to change their behavior or else your finding yourself frequently doing what your friends want to and what you do not (e.g., eat fast food, smoke, or listen to heavy metal rock music). As a consequence, people may vote with their feet and form new ties or strengthen ties with others with whom they have more in common.

2) norms/reference groups/culture/peer pressure: we often measure the reasonableness of our behavior against our friends. For example, if our teen friends have all had 6 sexual partners in the last year, then repartnering seems far more normal than if one is friends with a group that is heavily monogamous. Ditto with obesity or smoking or other possible traits or behaviors.

3) subconscious/imitation: as suggested with “emotion” below, sometimes we mirror others’ behavior or emotions without even thinking about it. C&F say it makes sense to think of people as subsconsciously reacting to those around them without being aware of any larger pattern. They talk about processes by which a “wave” at a sporting event takes place, or fish swim in unison, or geese fly in a V-formation, or crickets become synchronized — all of these happen by individuals mirroring those around them. And in the process, emergent properties of the group arise (much like a cake takes on the taste unlike any of its individual ingredients).

4) emotions: C&F note that emotions actually affect our physical being — our voices, our faces, our posture. In experiments, people actually “catch emotions”: others become happier by spending time around happy people or sadder by hanging out with depressed individuals. In experiments, smiling waiters get bigger tips. It seems quite plausible that cascades like loneliness, happiness, depression, etc. could spread simply from emotional states, independent of any information flowing through these friendships.

5) social invitations for shared action: friends often invite friends to do things — that’s part of friendship. For behaviors, one of the ways they can spread through networks is that, for example, thin friends could invite friends to exercise more, or obese friends could encourage friends to get ice cream together, or smokers could encourage others to leave the dance for a cig.

Connected notes that it is often hard, for example, to tell imitation and norms apart, “When a man gives up his motorcycle after getting hitched, is he copying his wife’s behavior (she doesn’t have a motorcycle) or adopting a new norm (the infernal things are unsafe?)”

Connected also notes how behaviors or attitudes can spread several social links out, even without the intervening link changing. They suggest that Amy could have a friend Maria who has a friend Heather. (Amy and Heather don’t know one another.) Heather gains weight. Maria, who really likes Heather, becomes less judgmental of her weight and gradually less judgmental of obesity in general. Maria doesn’t change her behavior but when Amy stops exercising with Maria, Maria is less likely to pressure her to resume. Thus Heather’s obesity changes Amy via Maria (by Maria no longer urging her to keep exercising), but Maria doesn’t change her behavior and Amy and Heather don’t know one another.

It’s interesting stuff to ponder and makes one think more expansively about the role and mechanisms of social capital. It also evokes a conversation with a Saguaro Seminar participant back in 1998 concerning whether black kids and white kids doing sidewalk painting together on the steps of an art museum could promote inter-racial trust, even if the black kids and white kids didn’t know each other, didn’t talk to one another and never met again. [My hunch is yes, depending on the strength of their pre-existing beliefs about inter-racial trust, but that talking could make the exchange far more powerful.] Another Saguaro participant wondered whether singing together in a chorus helps build social capital, even if one never has a conversation directly with another member of the chorus. (In the latter example, in addition to being highly unlikely, you are at least getting some non-verbal information over time from the other choral members about their trustworthiness: do they come regularly and on time, do they respectfully listen to and follow the choralmeister?)

I welcome your thoughts.

For more on the network effects, read pp. 24-30, 25-43 and 112-115 in Connected.

Mark Granovetter in a famous 1973 article “The Strength of Weak Ties” observed that it is our weaker social ties that are most likely to provide us access to information we don’t already know about: job leads, cross-fertilizing information that we can use to great advantage in our jobs, new opportunities, etc.

A recent paper by Sinan Aral and Marshall Van Alstyne says that Granovetter neglected to include frequency of contact. Yes, our weak ties are more likely per contact to provide us new information, but we contact our strong ties so much more often that a majority of novel information actually comes through those strong and demographically similar friends.

Aral and Van Alstyne analyzed nearly a year of e-mail from an executive recruiting firm (heavily dependent on e-mail for communication and where novel information was critical in finding the right candidates) and found that those with a tighter group of friends (which they define via less network diversity) actually got a higher ratio of new information per unit of time and produced higher revenue for the firm. As the authors hypothesized, recruiters with more diverse networks suffered a big drop in the volume of communication (what they call “channel bandwidth”). “Interestingly however, reductions in channel bandwidth associated with greater network diversity do not seem to be driven solely by time and effort costs of network maintenance, but also by the nature of the relationships in sparse networks.” Van Alstyne concludes: “a smaller number of high-bandwidth relationships can be good for you.”

Mario Luis Small, (University of Chicago, Sociology), who spoke this summer at our SCHMI 2010 workshop, has a compelling recent book that we commend. Mario is a wonderful person and a smart applied researcher, undertaking research with societal implications.

In his ground-breaking recent book Unanticipated Gains (Oxford University Press, 2009), Small both focuses on how important social capital is to the health of mothers but also uses the book to explore “how social capital is built” since he thought there was a lot of research on the importance of social capital and a dearth on how to create it. It represents a major advance in our collective knowledge.

He studied new mothers and daycare centers in the New York City area for two reasons:

They are prime place for observing new ties being formed since many American parents deal with these during in their lives, they have high turnover, and catch mothers at a phase of their life when they are often interested in and likely to make new ties (children are an important channel through which we make new ties). Daycare centers also come at a time in mothers’ life when they have big responsibilities (children) but low knowledge, which also makes networking very important (e.g., Who is a good local pediatrician? When do you worry about a rash? When should you start on formula? How warm does it need to be? What museums are child-friendly?).

Part of his research was about how social networks at daycare centers helped make mothers healthier and less depressed; he found significantly less depression in daycare centers where parents made more social ties and the quality of their information was much better.

But equally important was his conclusions about how social capital was built. This is an excerpt from a piece he wrote for RSA about his research.

Levels of commitment

We interviewed the directors of many different kinds of childcare centers – 23 in all, ranging from the commercial to the nonprofit, the secular to the religious, the corporate to the standalone – and observed what staff, children, mothers and fathers (though few of the latter were visible) did over the course of operations.

At the end of our study, nothing surprised us more than how much the centers differed in their social capital. In some, most mothers forged new friendships among the other parents; together, they organized parties, arranged play dates, attended movies and dinners, and developed what many of them referred to as a new community. Joining the center had measurably transformed their social networks…. In other centers, mothers knew few, if any, of the other parents; they did not party or dine with them, or babysit their children. These centers served as little more than drop-off and pick-up locations. In one rare example, the director had even tried to build social capital but failed: she threw a pizza party for parents to socialize and almost none of them attended.

Flickr photo by Jason L Park

Mario’s central question is “why” did some succeed when other centers failed in building social capital? He concludes that social capital was often the unintended consequence of an administrative policy.

The socially effective centers did not differ from the others in the amount of leisure time the mothers had at their disposal; in all of them, most mothers worked full-time. Race, class, lifestyle and neighborhood did not explain the difference, and nor did these centers have particularly heroic directors committed to creating a sense of community among the parents. On the contrary, few directors displayed any interest in building social capital for its own sake. Like the rest of us, they were busy; they had a center to run.

Instead, social capital typically emerged when directors were trying to accomplish some other task, one that gave parents opportunities to interact or incentives to cooperate. For example, many directors believed strongly that children should be exposed to zoos, museums, libraries, children’s parks and farms. But trips to these locations require many more adults than are needed in the classroom, to prevent children from sticking their hands in monkey cages, wandering off in parks or slipping into ponds at apple-picking expeditions. Since hiring more staff for these occasions was costly, the centers needed parents to attend. No parent volunteers, no field trips. Centers needed volunteers for other activities, too, such as sanding and painting playgrounds at the end of the year, contributing food for various ceremonies and raising money to keep tuition fees moderate. In some centers in low-income neighborhoods, mothers were expected either to raise a certain amount over the course of the year – usually about US$300 – or pay it out of pocket. To avoid paying the fee, parents had to volunteer for group fundraising activities, such as selling baked goods or holding raffles.

All of these activities – field trips, clean-ups, ceremonies and raffles – required interaction and socialisation with others; they obliged parents to meet, talk, exchange phone numbers, arrange schedules and get organized. As a result, the centers that imposed greater demands on parents provided opportunities and incentives that, over the course of weeks and months, stimulated the formation of social capital.

Mario also talks about how the daycare schedule helped build social capital. Some centers had strict drop-off and pick-up times, with fines often running at rates as high as $10 a minute for every minute that one was late. Other centers had lackadaisical attitudes toward drop-off and pick-up times. The centers with rigid times, in turn had parents all arriving at nearly the same time to drop-off and pick-up their children. Invariably, that time (just before or dropping off children) was a social capital gold mine: parents would ask other parents whether their child had had a certain behavioral problem, or would arrange playdates or would get advice about equipment, toys or books for their kid. Mothers would seek out useful connections to tap if they were unavoidably detained at work, got a flat tire, or were stuck in a train, to have that other parent to pick up their child. They might ask other mothers to babysit their children some time during the week in exchange for reciprocal favors. This is another example of administrative policies designed with no attention to social-capital-building that had big consequences. Every parent who didn’t form a social tie with others in a daycare center, regardless of their social class, cited flexible drop-off and pick-up times as the number one cause (and this was confirmed by the data).

Mario also found that the existence of a parent-teacher organization in a daycare center was a strong positive predictor of how much social capital was built.

The implication of Mario’s book is regardless of one’s organizational post, one should be more attuned to ways to build (or not destroy) social capital in the everyday policies; this is far more important than the intentional but infrequent organizational group get-together or pizza party. The pizza party is not counter-productive, but since it is a rarity, it’s unlikely to be as consequential as the daily rhythms and patterns of the organization.

One of Small’s interesting findings was that one of the reasons that the daycare centers were so successful in building social capital was their homophily: they tended to draw other parents of similar socio-economic backgrounds, partly through where the centers were located, through their pricing structure and through who was eligible for government-supported programs. Small speculated in a visit to Harvard (October 4, 2010) that the social capital gains exhibited by daycare centers would be less successful for a hypothetically new daycare center located in a mixed-income housing center and available only to its residents. He also speculated that it would lead to more task-oriented conflict, of the kind that he observed in researching Unanticipated Gains.

We highly recommend the book for those interested in rebuilding our stock of social capital. The book focuses much more on inter-organizational variance in building social capital (i.e., which organizational settings are more successful) than on within-organization variation in building social capital (i.e., who within a daycare center succeeds in building social ties). He agrees that more research is needed on this second question: the “mating” part of “meeting and mating.” His book focuses more on what about the organization creates an important opportunity structure for building social capital.

Small also noted that the ties generally being created at these daycare centers are a strange hybrid of strong and weak ties. Scholars like Granovetter focused on the strength of weak ties for accessing information (job leads, etc.) and the importance of strong ties for getting social support. In general, Small finds daycare centers produce “compartmental intimates”; daycare parents use these networks both for exchanging important information relating to their children, but because of the fact that young children share all kinds of private information about parenting and because parenting often relates to many other intimate things like the quality of one’s relationship with one’s spouse, these daycare friendships often provided strong social support and friends felt comfortable talking about many personal items that directly or indirectly related to their parenting. In this sense, these compartmental intimates offered some of the best of strong and weak ties.

Small engaged in an interesting dialogue with Robert Putnam about to what extent the focus on daycare centers obscures the role of agency (individuals’ efforts to build social capital). Does the existence of these daycare centers substitute for personal agency and effort? Does it compound inequalities in social capital creation. Small thinks in general that they daycare centers are likely to reduce the class-based inequalities in social ties and Putnam’s instinct is the opposite.

From a policy perspective, Mario Small’s work suggests that if one were hypothetically figuring out how to invest $5,000 in childcare per low-income resident in an area, one would be far better providing a voucher to be used for childcare in an organizational setting, rather than a voucher for family daycare or a $5000 voucher to the mother. Small found that the publicly-run centers also tended to maximize the social capital building: they typically had parent associations (founded in their Head Start roots) and ran a lot more field trips. They were also better about connecting parents to things like assistance if there domestic abuse issues, or access to dental and health exams.

It is already established that happiness and having social capital (friendships) are linked, but this research demonstrates that it matters how happy your friends are and that it is the happy friends that are causing your happiness rather than vice versa. Conversely, having unhappy friends over time makes you less happy.

They measured happiness with a 4-item construct: “I felt hopeful about the future”; “I was happy”; “I enjoyed life” and “I felt that I was just as good as other people.”

They found that happiness is a network phenomenon, clustering in groups of people that extend out to 3 degrees of separation (the friends’ friends of one’s friends), but with greater impact on friendships that are 2 or 1 degree of separation from you. Demonstrating the magnitude of this effect, co-author James Fowler noted, “if your friend’s friend’s friend becomes happy, that has a bigger impact on you being happy than putting an extra $5,000 in your pocket.”

They found that happiness spreads across a diverse array of social ties, from spouses to siblings to neighbors. They found no happiness effect of co-workers and found that nearby ties had a far greater influence than distant ties: for example, knowing someone who is happy, makes you 15.3% more likely to be happy, but having happy next-door neighbors makes you a full 34% more likely to be happy (much higher than having happy neighbors merely on your block). The optimal effect was for a happy friend living less than half a mile away, which boosts your chance of happiness by42%. In one of the study’s surprises, happy spouses (which one assumes live less than a half mile away!) only increased one’s chance of happiness by 8%. Part of the lower spouse effect is that happiness spreads more effectively through same sex relationships than relationships (romantic or not) between a man and a woman. (Gays take note!) Christakis and Fowler believe we may take emotional cues from people of our gender.

They observed that network characteristics (where you were in the network and how happy the people were around you) could independently predict which individuals would be happy years into the future.

They suggest that there may be an evolutionary basis for human emotions. Previous work noted that emotions like laughter or smiling seemed evolutionary adapted to helping people form social bonds. [They note: “Human laughter, for example, is believed to have evolved from the ‘play face’ expression seen in other primates in relaxed social situations. Such facial expressions and positive emotions enhance social relations by producing analogous pleasurable feelings in others.”]

happy people might change their behavior toward others (by being nicer or less hostile)

happy people might exude a contagious emotion (although this would have to be over a sustained time period)

Christakis and Fowler noted that the 3-degrees of separation impact observed in happiness was the same as for smoking and obesity (which also reached out 3 degrees). They wonder whether a “3-degrees of influence” extends to behaviors like depression, anxiety, loneliness, drinking, eating, exercise and other health-related activities.

So the next time you’re unhappy realize that you may be “infecting” your friends with unhappiness as well. Christakis’ work is suggesting that we need friends, but we also need to carefully pick friends that are happy and have healthy behaviors or we risk that their unhappiness and unhealthy behaviors will spread to us. The New York Times notes that one of the co-authors indicated that he now thinks twice about his mood knowing that it affects others. That said, he noted: “We are not giving you the advice to start smiling at everyone you meet in New York….That would be dangerous.”

While they think that face-to-face connection is important in spreading happiness (hence the decline of these effects with distance), they did a separate study of 1,700 Facebook profiles, where they found that people smiling in their photographs had more Facebook friends and that more of those friends were smiling. While the Facebook study is just an initial foray into the online word, Christakis thinks that it shows that some of these happiness findings might extend on social networking as well. And it would take longitudinal studies to determine whether our online activities are gradually eroding our need for face-to-face communication to spread happiness.

Note: Justin Wolfers (on the Freakonomics blog) is skeptical of this research. As he notes:

[It’s possible that it is not your friends’ happiness that is causing yours, but that “if you and I are friends, we are often subject to similar influences. If a buddy of ours dies, we’ll both be less happy. Or, less dramatically, if our favorite football team wins, we’ll both be happier. But this isn’t contagious happiness — it is simply a natural outcome of the shared experiences of people in the same social circles. Unfortunately, observational data cannot distinguish the headline-grabbing conclusion — that happiness is contagious — from my more mundane alternative: friends have shared emotional influences.”

Wolfers notes that a very careful article by Ethan Cohen-Cole and Jason Fletcher uses the same research design to show how it can lead to silly conclusions. Cohen-Cole and Fletcher find in another dataset that this approach shows “height, headaches, and acne are also contagious.” As Wolfers notes, it’s more likely that “the same jackhammer causing your headache is likely causing mine.” And the height finding is obviously not causal but more likely a function of homophily (people choosing similar friends).